Bringing SPARQL to compact data structures

  1. Delfina Ramos-Vidal
  2. Guillermo de Bernardo Roca
Libro:
Actas de las XXV Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2021): [Málaga, 22 al 24 de septiembre de 2021]
  1. Rafael Capilla (coord.)
  2. Maider Azanza (coord.)
  3. Miguel Rodríguez Luaces (coord.)
  4. María del Mar Roldán García (coord.)
  5. Loli Burgueño (coord.)
  6. José Raúl Romero (coord.)
  7. José Antonio Parejo Maestre (coord.)
  8. José Francisco Chicano García (coord.)
  9. Marcela Genero (coord.)
  10. Oscar Díaz (coord.)
  11. José González Enríquez (coord.)
  12. Mª Carmen Penadés Gramaje (coord.)
  13. Silvia Abrahão (col.)

Editorial: Sociedad de Ingeniería de Software y Tecnologías de Desarrollo de Software (SISTEDES)

Año de publicación: 2021

Congreso: Jornadas de Ingeniería del Software y Bases de Datos (JISBD) (25. 2021. Malaga)

Tipo: Aportación congreso

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Resumen

We present an architecture for the efficient storing and querying of large RDF datasets. Our proposal aims at storing RDF datasets in very reduced space while providing full SPARQL support. To do this, our solution builds on top of HDT, an RDF serialization framework, and its integration with the Jena query engine. We propose a set of extensions to this framework, in order to integrate a variety of space-efficient compact data structures as the underlying data representation, while taking advantage of the high-level capabilities to answer SPARQL queries. Our proposal provides a common mechanism to apply low-level data structures in complex query scenarios involving SPARQL queries, usually not supported by these solutions.

Fuente de los datos: Dialnet